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Manual bacteria classification is a tedious work which often needs abundant correlative data and also takes a great deal of time and energy. Combining pattern recognition and new neural network, we propose an approach of bacteria classification based on morphometrics using artificial neural network. The neural network is applied to extract the feature. The entropy sequence is taken as the feature...
Data integration is the problem of combining data residing at different sources, and providing the user with a unified view of these data. One of the critical issues of data integration is the detection of similar entities based on the content. This complexity is due to three factors: the data type of the databases are heterogeneous, the schema of databases are unfamiliar and heterogenous as well,...
With the growing computer networks, accessible data is becoming increasingly distributed. Understanding and integrating remote and unfamiliar data sources are important data management issues. In this paper, we propose to utilize self-organizing maps (SOM) clustering to aid with the visualization of similar columns, and integration of relational database tables and attributes based on the content...
Diversity among the team has been recognized as a very important characteristic in classifier combination. There are varied diversity measures. They can be categorized into two types, pairwise diversity measures and non-pairwise diversity measures. Above diversity measures are defined based on Oracle outputs of classifier. While using diversity measures to calculate diversity of classifiers that have...
The large collection of formal concepts can be a hedge of the application of FCA. Development of methods which help to overcome the problem of the huge size of concept lattice is thus an important task. This paper proposes clustering-based reduction algorithm for reducing the size of fuzzy concept lattices. At the end, experiment results show that the compression rate of the concept lattice and classifier...
Medical diagnosis can be viewed as a pattern classification problem: based a set of input features the goal is to classify a patient as having a particular disorder or as not having it. Performance of medical diagnosis is typically assessed in terms of sensitivity and specificity. In this paper we introduce a pattern classification system for medical diagnosis that is based on fuzzy logic and utilises...
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